@inproceedings{42bd4b5fb1884c81a189dc32c7d3bbbd,
title = "A Just-In-Time Keyword Extraction from Meeting Transcripts",
abstract = "In a meeting, it is often desirable to extract keywords from each utterance as soon as it is spoken. Thus, this paper proposes a just-in-time keyword extraction from meeting transcripts. The proposed method considers two major factors that make it different from keyword extraction from normal texts. The first factor is the temporal history of preceding utterances that grants higher importance to recent utterances than old ones, and the second is topic relevance that forces only the preceding utterances relevant to the current utterance to be considered in keyword extraction. Our experiments on two data sets in English and Korean show that the consideration of the factors results in performance improvement in keyword extraction from meeting transcripts.",
author = "Song, \{Hyun Je\} and Junho Go and Park, \{Seong Bae\} and Park, \{Se Young\}",
note = "Publisher Copyright: {\textcopyright} 2013 Association for Computational Linguistics; 2nd Workshop on Computational Linguistics for Literature, CLfL 2013 at the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2013 ; Conference date: 14-06-2013",
year = "2013",
language = "English",
series = "Proceedings of the 2nd Workshop on Computational Linguistics for Literature, CLfL 2013 at the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2013",
publisher = "Association for Computational Linguistics (ACL)",
pages = "888--896",
editor = "David Elson and Anna Kazantseva and Stan Szpakowicz",
booktitle = "Proceedings of the 2nd Workshop on Computational Linguistics for Literature, CLfL 2013 at the 2013 Conference of the North American Chapter of the Association for Computational Linguistics",
}